Brain Cancer

Assessment Tools of Radiation Skin Injury in Head and Neck Cancer: A Narrative Review of Preclinical and Clinical Studies.

Radiation skin injury (RSI) is an unavoidable side effect of radiotherapy that delays the treatment process and affects patients' quality of life. However, RSI is easily overlooked in clinical practice with unified assessment methods. Although over 20 types of clinical scales have already been reported, they were never collated and systematically reorganized. In this review, we collected and categ...

IDH enzyme inhibition in cancer therapy: mechanisms, mutational insights, and effects of IDH inhibitors in glioma, acute myeloid leukemia and chondrosarcoma.

Isocitrate dehydrogenase (IDH) enzymes have recently emerged as a highly promising target for therapeutic intervention in cancer treatment. Mutations in IDH genes result in the production of the oncometabolite, D-2-hydroxyglutarate (D-2HG), which contributes to tumorigenesis through epigenetic dysregulation, genomic methylation patterns and altered cellular metabolism. The functions of IDH1 and 2 ...

Leveraging proteomics and machine learning for mechanism and biomarker discovery on glioma progression and transformation: from LGG to GBM.

BACKGROUND: Glioma was the most common malignant tumor of the central nervous system in adults. Low-grade gliomas (LGGs) have a potential of grade pro...

Quantification of Ki-67 labeling index in pediatric brain tumor immunohistochemistry images.

Quantification of the Kiel 67 (Ki-67) labeling index (LI) is critical for assessing proliferation and prognosis in tumors but manual scoring remains a...

Hybrid Aquila optimizer-Harris Hawks optimization for CNN hyperparameter tuning in brain tumor classification.

Magnetic resonance imaging (MRI) is hard to categorize properly in terms of interclass similarity, there is data imbalance, and sensitive clinical dec...

Pathology Public Datasets for Artificial Intelligence: A Systematic Review.

Histopathology plays a crucial role in the diagnosis of many diseases, especially cancers, for which the correct classification of tissue samples sign...

SMC4/SMAD3/NF-κB axis drives cervical cancer progression and radioresistance via DNA damage repair and immune modulation.

OBJECTIVE: Cervical cancer remains a significant global health burden, with the molecular determinants of its progression and therapeutic resistance n...

Deep Learning Reconstruction on Quantitative Analysis in Brain Tumors With Diffusion-Weighted Imaging and Dynamic Susceptibility Contrast Imaging.

BACKGROUND: Although deep learning reconstruction (DLR) has been shown to improve image quality in MRI, its impact on quantitative physiologic paramet...

Machine learning model on multi-omics data enables risk stratification and identifies molecular heterogeneity and therapeutic targets in glioblastoma.

Multimodal Deep Learning-Based Screening of Degenerative Temporomandibular Joint Disease Using 2D Radiography: A Cost-Effective and Low-Radiation Approach.

OBJECTIVES: This study aimed to develop and preliminarily validate a multimodal deep learning model based on two-dimensional maxillofacial imaging for...

Lanthanide-Doped Organic Framework Sensor Array Coupled with Machine Learning for Minimally Invasive Glioma Diagnosis via Cerebrospinal Fluid Biopsy.

Glioblastoma multiforme (GBM), the most malignant subtype of glioma, poses significant diagnostic challenges due to limitations in current methods, su...

Multiplexed Microenvironment-Responsive Probes Enable Rapid Glioblastoma Cell Line Analysis.

Accurate distinguishing the phenotype of glioblastoma (GBM) cell lines remains challenging in clinical diagnostics, particularly for rapid intraoperat...

Improving MRI-based differentiation of brain metastasis, glioblastoma, and primary CNS lymphoma using deep learning.

The DNA-Based Disease Diagnosis Model with Strand Displacement Reaction.

MicroRNAs (miRNAs) serve as crucial biomarkers in disease diagnosis. Although silicon-based electronic machine learning models provide efficient means...

Integrated analysis of therapeutic strategies and prognostic factors in advanced lung adenocarcinoma: Retrospective study with emphasis on gene assays, multimodality treatment approaches and predictive machine learning models.

Patients with advanced lung adenocarcinoma have a range of treatment options, including targeted therapy and gene assay-guided chemotherapy. The aim o...

Application of treatment response assessment maps (TRAMs), based on delayed-contrast MRI for radiomic characterization of breast lesions.

Dynamic contrast-enhanced (DCE) breast MRI is a highly sensitive modality for detecting breast cancer, but its limited specificity often leads to fals...

Automatic Hepatic Steatosis Quantification using Low-Dose CT with deep learning-based noise reduction and CT Fat Fraction Analysis Software.

OBJECTIVES: To evaluate the accuracy of CT-derived fat fraction (CDFF) software for quantifying hepatic steatosis at various radiation doses, using MR...

Intelligent model for stratification of acute radiation syndrome severity in humans.

PURPOSE: The aim of this study was to develop and compare two intelligent model for stratifying the severity of acute radiation syndrome (ARS) in huma...

Decoding the Glioblastoma Microenvironment: AI-Driven Analysis of Cellular MRI Signatures for Targeted Therapy.

Glioblastoma (GB), the most aggressive primary brain tumor, is characterized by profound inter- and intratumoral heterogeneity and a highly immunosupp...

MRI In Vivo Detection of Amyloid-β Protein Deposition in Different Brain Regions of Patients with AD and MCI.

To investigate a non-invasive magnetic resonance imaging (MRI)-based method for detecting amyloid-β (Aβ) protein deposition in different brain regions...